Skip to main content

Table 2 Accuracy and Confidence values of global alignment

From: The ranging of amino acids substitution matrices of various types in accordance with the alignment accuracy criterion

   30 PAM    60 PAM  
Matrix Gap open Gap extention Accuracy Confi-dence Gap open Gap extention Accuracy Confi-dence
PAM30 18.0 2.0 0.9910 0.9907 25.0 2.0 0.9604 0.9600
PAM60 17.0 1.0 0.9916 0.9911 21.0 1.0 0.9610 0.9607
PAM120 13.0 1.0 0.9914 0.9908 13.0 1.0 0.9621 0.9599
PAM250 9.0 1.0 0.9901 0.9894 13.0 1.0 0.9610 0.9575
Blosum45 15.0 1.0 0.9901 0.9893 14.0 1.0 0.9559 0.9531
Blosum50 14.0 1.0 0.9902 0.9895 17.0 1.0 0.9563 0.9533
Blosum62 16.0 1.0 0.9906 0.9900 19.0 1.0 0.9575 0.9549
Gonnet250 11.0 1.0 0.9899 0.9890 11.0 1.0 0.9551 0.9514
Gonnet_p 7.0 1.0 0.9879 0.9864 10.0 1.0 0.9460 0.9398
Optima 10.0 1.0 0.9899 0.9891 14.0 1.0 0.9557 0.9520
VTML250 10.0 1.0 0.9894 0.9885 12.0 1.0 0.9555 0.9515
MIQS 11.0 1.0 0.9897 0.9888 15.0 1.0 0.9564 0.9527
Pfasum050 14.0 1.0 0.9899 0.9890 16.0 1.0 0.9574 0.9542
Pfasum100 11.0 1.0 0.9901 0.9892 14.0 1.0 0.9573 0.9542
Crooks 13.0 1.0 0.9900 0.9893 17.0 1.0 0.9555 0.9524
CCF53 11.0 1.0 0.9900 0.9892 13.0 1.0 0.9563 0.9534
Moll60 12.0 1.0 0.9900 0.9893 16.0 1.0 0.9564 0.9531
Johnson 18.0 1.0 0.9904 0.9899 23.0 1.0 0.9564 0.9547
Prlic 18.0 1.0 0.9896 0.9889 24.0 1.0 0.9532 0.9503
Blake 22.0 1.0 0.9880 0.9879 30.0 1.0 0.9468 0.9458
Benner 9.0 1.0 0.9878 0.9867 12.0 1.0 0.9452 0.9407
Miyazawa 21.0 1.0 0.9864 0.9855 22.0 1.0 0.9432 0.9408
Data set   120 PAM    Bali Base  
Matrix Gap open Gap extention Accuracy Confi-dence Gap open Gap extention Accuracy Confi-dence
PAM30 30.0 4.0 0.8065 0.7991 24.0 4.0 0.6257 0.6215
PAM60 26.0 3.0 0.8174 0.8080 20.0 3.0 0.6301 0.6236
PAM120 19.0 1.0 0.8189 0.8152 16.0 2.0 0.6287 0.6205
PAM250 17.0 1.0 0.8325 0.8241 11.0 2.0 0.6310 0.6240
Blosum45 22.0 1.0 0.7949 0.7855 13.0 1.0 0.6495 0.6473
Blosum50 21.0 1.0 0.7925 0.7866 16.0 2.0 0.6523 0.6433
Blosum62 24.0 2.0 0.7972 0.7877 19.0 2.0 0.6533 0.6455
Gonnet250 16.0 1.0 0.8129 0.8037 11.0 1.0 0.6592 0.6541
Gonnet_p 13.0 1.0 0.7870 0.7729 7.0 1.0 0.6470 0.6353
Optima 17.0 1.0 0.7907 0.7830 13.0 1.0 0.6515 0.6463
VTML250 15.0 1.0 0.8110 0.8017 11.0 1.0 0.6544 0.6486
MIQS 18.0 1.0 0.8046 0.7964 13.0 1.0 0.6518 0.6479
Pfasum050 21.0 1.0 0.8015 0.7939 15.0 2.0 0.6599 0.6507
Pfasum100 18.0 1.0 0.7973 0.7891 12.0 1.0 0.6527 0.6499
Crooks 18.0 2.0 0.7921 0.7823 14.0 2.0 0.6553 0.6470
CCF53 18.0 1.0 0.7923 0.7841 14.0 1.0 0.6488 0.6429
Moll60 19.0 1.0 0.7819 0.7762 12.0 2.0 0.6484 0.6403
Johnson 29.0 2.0 0.8011 0.7935 19.0 3.0 0.6524 0.6456
Prlic 13.0 1.0 0.7870 0.7729 18.0 2.0 0.6476 0.6427
Blake 30.0 4.0 0.7608 0.7547 24.0 3.0 0.6444 0.6419
Benner 16.0 1.0 0.7385 0.7282 10.0 1.0 0.5917 0.5848
Miyazawa 30.0 2.0 0.7539 0.7449 20.0 3.0 0.6024 0.5936
  1. The optimal values of the alignment quality (Accuracy, Confidence) with the corresponding values of the penalty function parameters (GOP, GEP) are given. Data were obtained for all matrices examined, on test sets of the generated sequences: 30 PAM, 60 PAM, 120 PAM, and on Balibase [18] sequences. A full set of alignment quality values for the entire set of tested GOP and GEP parameters is given in Additional files 1, 2: Table S1, Table S2